Comparing Future Red Tide Scenarios

For this test run, I took the SEDAR Red Grouper stock assessment and used SSMSE to introduce future red tide events in the OM and EM. There were 6 total scenarios:

1. default: the base stock assessment with red tide events in 2005 and 2014.
   
2. red tide random 10: I used a custom function to generate 10 random red tide events in the projected years.
   
3. red tide random 25: I used a custom function to generate 25 random red tide events in the projected years.
   
4. red tide regular 3: I added a red tide event every 3 years.
5. red tide regular 5: I added a red tide event every 5 years.
6. red tide regular 5 mortality 5: I added a red tide event every 5 years and set the OM mortality to 0.5.

Import the results and summary files from the cloud.

Reviewing time series plots

List of the things we can plot with the ts_plot_variable function:

 [1] "year"        "Area"        "Seas"        "Bio_smry"    "SpawnBio"   
 [6] "Recruit_0"   "retainB_1"   "retainN_1"   "retainB_2"   "retainN_2"  
[11] "retainB_3"   "retainN_3"   "retainB_4"   "retainN_4"   "retainB_5"  
[16] "retainN_5"   "deadB_1"     "deadN_1"     "deadB_2"     "deadN_2"    
[21] "deadB_3"     "deadN_3"     "deadB_4"     "deadN_4"     "deadB_5"    
[26] "deadN_5"     "F_1"         "F_2"         "F_3"         "F_4"        
[31] "F_5"         "SPRratio"    "rec_dev"     "raw_rec_dev" "model_run"  
[36] "iteration"   "scenario"   

Here are the basic plots:

Red tide mortality

Red tide dead biomass

Spawning Stock Biomass

Retained Biomass

Long-Term SSB and Violin plots

These plots are similar to Doering et al. 2023

This plot takes the longest to process. It generates a plot of the SSB variation by scenario. Then it creates a series of violin plots with the OM and MS for Long-term average catch, Long-term catch variability, Short-term average catch, and Long-term average SSB.

Relative SSB

Catch Variability plot 1

Long-term Catch Variability plot

This plot is similar to the Long-term catch variability plot [2] in the previous chunk, but this produces a plot of the coefficient of variation instead of Catch (metric tons).

Final patchwork plot

This just combines the previous plots into a nice 2 by 2 patch work for easier viewing.

Reviewing derived quantities

Some of the same plots above but derived. Below is a list of all the derived quantity variables:

 [1] "Value.SSB"          "Value.Recr"         "Value.SPRratio"    
 [4] "Value.F"            "Value.Bratio"       "Value.ForeCatch"   
 [7] "Value.OFLCatch"     "Value.ForeCatchret" "Value.lnSPB"       
[10] "year"               "model_run"          "iteration"         
[13] "scenario"          

Recruitment

SSB

SPR Ratio

B Ratio

F

Term Plots

default

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

General Brainstorm:

Quantify how often the stock crashes from red tide events? Quantify the loss of catch from each red tide event, then the average loss.

 [1] "year"        "Area"        "Seas"        "Bio_smry"    "SpawnBio"   
 [6] "Recruit_0"   "retainB_1"   "retainN_1"   "retainB_2"   "retainN_2"  
[11] "retainB_3"   "retainN_3"   "retainB_4"   "retainN_4"   "retainB_5"  
[16] "retainN_5"   "deadB_1"     "deadN_1"     "deadB_2"     "deadN_2"    
[21] "deadB_3"     "deadN_3"     "deadB_4"     "deadN_4"     "deadB_5"    
[26] "deadN_5"     "F_1"         "F_2"         "F_3"         "F_4"        
[31] "F_5"         "SPRratio"    "rec_dev"     "raw_rec_dev" "model_run"  
[36] "iteration"   "scenario"   

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

More plots

If a red tide event happens in the last 3 years of the simulation, Stock Synthesis overestimates the mortality event by X.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Weird plots

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Mean ratio plots

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Terminal year plots

Only red tide years

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

B/W terminal year plots

All years.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Fishing terminal year plots

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Fishing terminal year plots all years

Plots of all years instead of just red tide years

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Terminal year with added mean line

Only years with red tide events

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Fishing terminal year plots

I was redoing the mean lines and sds, and noticed that the EM:OM ratio would be NA if the EM F is zero (happens a lot in F_5). I added those NAs back in as zeros and it dramatically dampens the F_5 “spike”. So I filtered this data to only years where a red tide occurred to highlight that the spike in the terminal year trend is only relevant to red tide years.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

New complex Ratio plots

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

All years, biomass ratios

I was redoing the mean lines and sds, and noticed that the EM:OM ratio would be NA if the EM F is zero (happens a lot in F_5). I added those NAs back in as zeros and it dramatically dampens the F_5 “spike”. So I filtered this data to only years where a red tide occurred to highlight that the spike in the terminal year trend is only relevant to red tide years.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Red tide years, biomass ratio

This is the biomass ratios in just the red tide years so the trends are more clear in Fleet 5.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Red tide years, biomass ratio, just Com and Rec Retained and Discards

This is the biomass ratios in just the red tide years so the trends are more clear in Fleet 5.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Exploring Recruitment

Recruitment DQ

Recruitment TS

“rec_dev” “raw_rec_dev” “Recruit_0”

rec_dev TS

raw rec_dev TS

Recruitment ratios, all years

This is the biomass ratios in just the red tide years so the trends are more clear in Fleet 5.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Terminal year recruitment ratios, all years

This is the biomass ratios in just the red tide years so the trends are more clear in Fleet 5.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Terminal year recruitment ratios, red tide years

This is the biomass ratios in just the red tide years so the trends are more clear in Fleet 5.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Terminal year rec_devs ratios, all years

This is the biomass ratios in just the red tide years so the trends are more clear in Fleet 5.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Terminal year rec_devs ratios, red tide years

This is the biomass ratios in just the red tide years so the trends are more clear in Fleet 5.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Terminal year SSB ratios, red tide years

This is the biomass ratios in just the red tide years so the trends are more clear in Fleet 5.

10 random red tides

25 random red tides

Red tide every 3 years

Red tide every 5 years

Mortality = 0.5

Inspired by Wetzel and Punt et al. 2011

I am going to attempt to make their Relative Error Plots.

RE = (E - T) / T

Variables of interest:

F_5, Recruit_0,

Recruitment

SpawnBio

Com F

Rec F

F_5

Com Catch

Rec Catch

Red Tide Discards

Warning: Removed 28 rows containing non-finite outside the scale range
(`stat_boxplot()`).

Warning: Removed 540 rows containing non-finite outside the scale range
(`stat_boxplot()`).

Warning: Removed 547 rows containing non-finite outside the scale range
(`stat_boxplot()`).

Then I may attempt to calculate RMSE

Exploring Indecies

I was able to put cpue from one scenario/iteration but it doesn’t get projected past 2017.